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Abstract

Where observers concentrate their gaze during visual search depends on several factors. The aim here was to determine how much of the variance in observers’ fixations in natural scenes can be explained by local scene color and how that variance is related to viewing bias. Fixation data were taken from an experiment in which observers searched images of 20 natural rural and urban scenes for a small target. The proportion R2 of the variance explained in a regression on local color properties (lightness and the red–green and yellow–blue chromatic components) ranged from 1% to 85%, depending mainly on how well those properties were consistent with observers’ viewing bias. When viewing bias was included in the regression, values of R2 increased, ranging from 62% to 96%. By comparison, local lightness and local lightness contrast, edge density, and entropy each explained less variance than local color properties. Local scene color may have a much stronger influence on gaze position than is generally recognized, capturing significant aspects of scene structure on target search behavior.

Figures (5)

Examples of natural scene images and observed and fitted spatial distributions of observers’ fixations. The first row shows four of the scenes from the 20 used in the experiment, including those producing the best fit (leftmost image) and worst fit (rightmost image). In the second image, the target is shown arrowed, and in the center of the close-up on the bottom right. The middle row shows the smoothed observed fixation distributions. The bottom row shows the estimated fixation distribution obtained by fitting the distributions of local color properties in each scene [see Eq. (1) in text] and the resulting percentage R2 of variance explained at the bottom left. Values of R2 were adjusted for the degrees of freedom in each fit. The smoothing was based on a locally weighted quadratic regression (loess) with a Gaussian kernel of 2.5-deg standard deviation. Higher frequencies of fixations are indicated by darker contours. Positions of maxima are indicated by crosses.

Observed and fitted viewing-bias distributions for the scenes shown in Fig. 1. The first row shows the bias distribution estimated by pooling fixations over scenes and observers (and therefore common to all scenes). The second row shows the estimated fixation distribution obtained by fitting the distributions of local color properties in each scene [see Eq. (2) in text]. Other details as for Fig. 1.

Percentage R2 of variance in fixations explained by local color properties as a function of percentage R2 of variance in viewing bias explained by local color properties. Each symbol represents a pair of R2 values for a single scene out of the 20 tested. The dotted line is a linear regression. Data for the scenes in Fig. 1 are shown labeled. Values of R2 were adjusted for the degrees of freedom in each fit.

Observed spatial distributions of successive fixations for the scenes shown in Fig. 1. The first, second, third, and fourth rows show the smoothed first, second, third, and fourth fixation distributions. The values of the coefficients of determination R2 averaged over all six possible pairings of successive distributions within a scene (i.e., 3×2×1) are shown at the bottom left in the bottom row. Other details as for Fig. 1.

Percentage R2 of variance in fixations explained by different scene properties. Mean values of R2 are shown for fits to the fixation distributions in each scene of local lightness entropy, contrast, and edge density, local lightness, and color and color combined with viewing bias (for definitions, see Section 2.G). Symbols represent values averaged over 20 scenes, and horizontal bars ±1 standard error of the mean. Values of R2 were adjusted for the different d.f. in each fit.